Simultaneous model discrimination and parameter estimation in dynamic models of cellular systems.

ABSTRACT:

Background

Model development is a key task in systems biology, which typically starts from an initial model candidate and, involving an iterative cycle of hypotheses-driven model modifications, leads to new experimentation and subsequent model identification steps. The final product of this cycle is a satisfactory refined model of the biological phenomena under study. During such iterative model development, researchers frequently propose a set of model candidates from which the best alternative must be selected. Here we consider this problem of model selection and formulate it as a simultaneous model selection and parameter identification problem. More precisely, we consider a general mixed-integer nonlinear programming (MINLP) formulation for model selection and identification, w

SUBMITTER: Rodriguez-Fernandez M 

PROVIDER: S-EPMC3765209 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature